# Sr Technical Product Manager - HPC Integration at QuEra Computing

> United States · Senior · Product · open. Source: https://alderhq.app/jobs/greenhouse%3Aqueracomputinginc%3A5081845008 (read 2026-11-04).

## Facts (observed)

- Company: [QuEra Computing](https://alderhq.app/companies/quera-computing)
- Location text: Boston, MA, USA; Boston
- Where it can be done from (inferred): United States (evidence: "Location: Boston, MA, USA; Boston")
- Posted: 2026-01-22 (286 days ago)
- First seen by alder: 2026-11-02 · last verified: 2026-11-04
- Reposted: 0 times · edited: 0 times
- Apply on the employer's site: https://job-boards.greenhouse.io/queracomputinginc/jobs/5081845008
- Skills listed (inferred): Node.js, AWS, GCP, Azure, Kubernetes

## Pay and sponsorship

- Posted pay: not posted
- Market band for similar posted roles (Boston, n 43): p25 $160k, median $160k, p75 $179k

## Description (the employer's text)

1. Mission of the Role

To define, validate, and execute the integration strategy for QuEra’s quantum systems within classical HPC/AI infrastructure — identifying use cases, technical requirements, and the right ecosystem partners across the full value chain.

2. Core ResponsibilitiesA. Use Case Discovery & Technical Research

- Deeply study academic and industry papers on quantum-classical hybrid workflows, quantum HPC/AI Data center integration, and the accelerations of AI for Science/Quantum discovery via quantum computing.
- Identify high-value use cases (e.g., quantum chemistry, materials discovery, cryptoanalysis, optimization) relevant to HPC and AI centers
- Translate theoretical research into practical product requirements — what integration, APIs, or software layers are needed to run these use cases.
- Collaborate with research teams to maintain technical credibility when engaging HPC customers or partners.
- Co-design solutions with lighthouse customers to verify the feasibility
A. Value Chain Mapping

- Use the HPC value chain framework (hardware → integration → data center → middleware → workloads → services) to:
- Map current players (AWS, HPE, NVIDIA, etc.) and their quantum readiness.
- Identify where quantum computing fits within this chain (e.g., as accelerator hardware, a cloud service, or a hybrid scheduler layer).
- Define which layers QuEra should own vs. partner — e.g.:
- Own: Quantum hardware, quantum control stack.
- Partner: Data center operations, cloud orchestration, middleware, hybrid execution APIs.
B. Requirements Definition

- Gather technical and operational requirements from HPC and AI center operators:
- Power, cooling, networking, physical integration.
- Scheduler integration (Slurm, PBS, AWS Batch, Kubernetes).
- Security, compliance, and monitoring needs.
- Define product specifications for Quantum-Classical Integration Interfaces (QCII) — the APIs, SDKs, and orchestration layers that enable hybrid workloads.
C. Partner Identification & Engagement

- Build a partner map for each value chain layer:
- Hardware partners: compute (NVIDIA, AMD, ARM), interconnect (Infiniband), storage (DDN, AWS FSx).
- Cloud/HPC providers: AWS, Microsoft Azure, Google Cloud, HPE Cray, NVIDIA DGX Cloud.
- System Integrators: Dell, HPE
- Middleware/software partners: Slurm
- Application/industry partners
- Lead technical discussions and joint proof-of-concept programs with selected partners.
- Evaluate integration options — e.g., on-prem quantum node vs. cloud-connected quantum service.
D. Product Strategy & Roadmapping

- Define a phased integration roadmap for quantum into HPC centers and AI data center:
- Simulation stage: Run QuEra simulators on HPC clusters.
- Hybrid orchestration stage: Enable joint scheduling of classical + quantum workloads.
- Native quantum accelerator stage: Deploy QuEra hardware within HPC/AI center or connect over high-speed link.
- Balance build/partner decisions at each stage, ensuring scalability and differentiation.
### F. Communication & Stakeholder Management

- Act as the bridge between technical R&D, engineering, business development, and external partners.
- Create clear documentation (requirements docs, partner briefs, integration specs).
- Communicate effectively with HPC operators and enterprise customers (translating quantum complexity into operational language).
3. Key Skills and BackgroundTechnical Depth: Background in physics, computer engineering, or computational science; understanding of quantum computing principles and HPC architecture (Slurm, MPI, GPUs, network topology).

Product Management: Experience defining product requirements, roadmaps, and partner strategies in deep tech or HPC environments.

Ecosystem Awareness: Knowledge of cloud and data center ecosystems — AWS, NVIDIA, Intel, HPE, etc.

Cross-Functional Leadership: Ability to collaborate with quantum hardware engineers, software developers, and business teams.

Partnering & Alliances: Experience building technical partnerships and evaluating technology fit.

Communication: Skilled at simplifying deep-technical material for non-specialist executives and partners.

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Data: alder (https://alderhq.app). Cite https://alderhq.app/jobs/greenhouse%3Aqueracomputinginc%3A5081845008 and the date you read it. Observed facts come from the employer's own listing; location reach, level, family and skills are inferences.